The present invention disclosed herein relates to image signal processing. In particular, the present invention disclosed herein relates to method and device for evaluating random noises of image signals.
With the rapid increase in the spread of portable apparatuses and digital cameras, demand for image sensors in the industry of portable electronic devices is consequently increasing. As customers are requiring high-quality products convenient in portability, manufacturers of digital products are pursuing miniaturization and high quality of all components embedded in products.
Developers of image sensors are trying to scale down a size of photodiodes of the image sensor for higher resolution and miniaturization. Image sensors are divided into charge-coupled devices (CCDs) and complementary metal-oxide-semiconductor image sensors (CISs). From trends in dimensional changes of photodiodes over several years, it can be seen that the shrink-down of photodiodes in the CIS is progressing faster than in the CCD. Otherwise, resolution of the image sensor continues to increase.
Those trends in miniaturization and higher resolution of image sensors are permissible based on the advancement of microscopic circuit design technology and semiconductor fabrication technologies. Scaling down a line width of a circuit to reduce a size of a photodiode of an image sensor varies resultant values of typical items used for evaluating characteristics of the image sensor. Typical items for evaluating characteristics of the image sensor are sensitivity, dynamic range, signal-to-noise ratio (SNR), noise, and so forth. The most significant evaluation item is ‘noise’ because a smaller size of photodiode causes deterioration of noise characteristic due to a lower optical signal level. Thus, there are required new ways of improving an optical signal level, for which the noise is the most important factor to determine improvement of the optical signal level. Further, the noise significantly affects results of image characteristic evaluation items. For example, an evaluation result for a dynamic range or SNR is variable in accordance with a noise evaluation data.
The noise, being important as a characteristic evaluation item of the image sensor, is classified into fixed pattern noise (FPN) and random noise (RN). The FPN means noise fixedly representing an output signal gap between adjacent photodiodes in an output image. The RN means noise continuously changing along time. The FTN of these two noise types are improvable by using high-tech signal processing.
A general algorithm for evaluating RN calculates a standard deviation of pixel output values on the same position, and calculating a root-mean-square (RMS) of all pixels. Such an RN evaluation algorithm requires a large-capacity memory for storing image data output from all pixels. As the number of pixels increases, a memory size increases by geometric progression.